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- W4386412314 abstract "Vectors are generally compared through the comparison of the exact values of their components. Existing techniques only compare two vectors and are limited by many factors for the comparison of vectors having different dimensions. This paper attempts to overcome all these limitations by proposing a new technique based on hidden Markov models which enhances existing techniques by giving them the ability to compare two finite sets of vectors, each containing vectors having different dimensions, while precising the set of targeted properties on which the comparison should be performed. Classification experiments conducted on three online available custom datasets demonstrated that when the suitable set of targeted properties is selected, the proposed approach outperforms existing techniques with accuracy gains reaching +82.3%." @default.
- W4386412314 created "2023-09-05" @default.
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- W4386412314 date "2023-01-01" @default.
- W4386412314 modified "2023-10-04" @default.
- W4386412314 title "Enhancing vector comparison using HMMs" @default.
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- W4386412314 doi "https://doi.org/10.1109/access.2023.3312019" @default.
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